Measurement of Size Distribution of Blasted Rock Using Digital Image Processing

JKAU: Eng. Sci., Vol. 20 No. 2, pp: 81-93 (2009 A.D. / 1430 A.H.)

81

Measurement of Size Distribution of Blasted Rock Using

Digital Image Processing

F.I. Siddiqui, S.M. Ali Shah and M. Y. Behan

Department of Mining Engineering,

Mehran University of Eng. and Tech., Jamshoro, Pakistan

[email protected]

Abstract. The purpose of this study is to measure the size distribution

of blasted rock using the digital image processing software “Split-

Desktop system” in order to evaluate the efficiency of blasting

operation. Site of study is a limestone quarry producing limestone for

cement manufacturing. Fragmentation is the ultimate measure of

efficiency of any production blasting operations. The degree of

fragmentation plays an important role in order to control and minimize

the loading, hauling, and crushing costs.

The size distribution analysis of the rock fragmentation by

sieving is a direct and accurate method but it is very time consuming

and costly. Fragmentation analysis by digital image processing is a

low cost and quick method. Split system is one of the digital image

processing software developed to compute the size distribution of

fragmented rock from digital images. In this study, size distributions

were analyzed by using Split Desktop ® system. In the analysis, the

mean fragment size obtained is 149.76 mm and top-size 1057.44 mm.

25% of the fragments are below 30 mm. A thorough appraisal of

blasting operation is suggested to enhance the efficiency of all the

post-blast operations such as Loading, Hauling, crushing and Grinding

and also reduces the cost of secondary breakage.

Keywords: Fragmentation, Rock blasting, Digital image processing,

Split-Desktop

1. Introduction

The key objective of production blasting is to achieve optimum rock

fragmentation. The degree of rock fragmentation plays an important role

in order to control and minimize the overall production cost including

F.I. Siddiqui, et al. 82

loading, hauling, and crushing costs. Optimum rock fragmentation

improves the energy efficiency of comminution (Crushing & Grinding)

processes and thousands of kilowatt-hours energy per year can also be

saved.

Blasting is the first step of the size reduction in mining and it is

followed by crushing and grinding unit operations. The efficiency of

these unit operations is directly related to the size distribution of

muckpile. Therefore, reliable evaluation of fragmentation is a critical

mining problem[1]

.

Production of finer fragments in blasting operation reduces the work-

load of primary crushers; therefore increasing the crusher efficiency and

reducing the crushing cost. Also crushing rate per hour will increase.

2. Size Distribution Analysis Using Digital Image Processing

Measurement of fragment size of blasted rock is considerably

important in order to evaluate the efficiency of the production blasting

operation. There are several methods of size distribution measurement

and fall under two broad categories; direct method and indirect methods.

The sieve analysis is the direct and accurate method of measuring size

distribution. Although it is the most accurate technique among others, it

is not practical for such a large scale due to being both expensive and

time consuming. For this reason, indirect methods which are

observational, empirical and digital methods have been developed[1]

.

Observational methods include the visual observations of muckpiles

immediately following the blasting. It is widely used by blasting

engineers to arrive at an approximation.

In some empirical models such as Larsson’s equation, SveDeFo

formula, KUZ-RAM model, etc, blasting parameters are considered to

determine the size distribution of blasted rock[2]

.

Recent fragmentation assessment techniques using digital image

processing program allow rapid and accurate blast fragmentation size

distribution assessments. Digital image software was developed through

the 1990s and at present it is a worldwide accepted tool in the mining and

mineral processing industries. Its main advantage is that it can be used on

a continuous basis without affecting the production cycle, which makes it

the only practical tool for evaluating fragmentation of the run of mine.

Measurement of Size Distribution of Blasted Rock …

83

However, some errors are also associated with the digital image

analysis. It is extremely hard to obtain accurate estimates of rock

fragmentation after blasting. Following are the main reasons for error in

using image analysis programs[3]

.

a. Image analysis can only process what can be seen with the eye.

Image analysis programs cannot take into account the internal rock, so

the sampling strategies should be carefully considered.

b. Analyzed particle size can be over-divided or combined; which

means larger particles can be divided into smaller particles and smaller

particles can be grouped into larger particles. This is a common problem

in all image-processing programs. Therefore, manual editing is required.

c. Very fine particles can be underestimated, especially from a

muckpile after blasting. There is no good answer to avoid these

problems.

There are several softwares namely SPLIT, WipFrag, GoldSize,

FragScan, TUCIPS, CIAS, PowerSieve, IPACS, KTH, WIEP, etc. that

are commercially available to quantify the size distribution. The accuracy

of these systems varies between 2 % to 20 %[4]

. In this investigation, the

SPLIT-DESKTOP system was used for size distribution computation.

2.1 SPLIT System for Size Distribution Analysis

Split system is an image-processing program designed to calculate

the size distribution of rock fragments through analyzing digital

grayscale images. Digital grayscale images can be acquired manually

through use of a digital camera, individual frame capture from video or

through scanned (digitized) photographs.

The Split software is the result of over nine years of research and

development at The University of Arizona. Split-Desktop combines the

elements of Split, a software program copyrighted by the Arizona Board

of Regents and exclusively licensed for further development and

marketing to Split Engineering, LLC, with elements and research input

from Julius Kruttschnitt Mineral Research Centre of Brisbane,

Queensland, Australia. The original Split software programs were written

using source code modifications to NIH Image, a public domain image-

processing program developed by Wayne Rasband at the United States

National Institutes of Health[5]

.


There are two formats of Split system, one is fully automated and

operates continuously on images taken from a conveyor belt. The other is

the Split-Desktop® software refers to the “user-assisted” off-line version

of the Split programs that can be operate on saved images.

The subject of these images can be a muckpile, haul truck, leach pile,

draw point, waste dump, stockpile, conveyor belt, or any other location

where clear images of rock fragments can be obtained. Once the images

are taken and saved to a computer, the Split-Desktop software has five

progressive steps for analyzing each image[6]

.

The first step in the program allows the scale to be determined for

each image taken in the field. The second step performs the automatic

delineation of the fragments in each of the images that are processed. The

third step allows editing of the delineated fragments to ensure accurate

results. The fourth step involves the calculation of the size distribution

based on the delineated fragments. Finally, the fifth step concerns the

graphing and various outputs to display the size distribution results.

3. Measurement of Size Distribution of Blasted Rock

at Limestone Quarry

Site of investigation is a limestone quarry producing limestone for

cement manufacturing. The mining method at the quarry uses the

traditional open pit practice of drilling and blasting a planned rock bench,

loading of material with wheel loaders, and hauling to the primary

crusher by heavy duty rear-dump trucks.

3.1 Description of Site

The limestone quarry belongs to Dewan cement (formerly Pak-land

cement) located near Karachi, Pakistan. The limestone deposit is of

Miocene age and belongs to Gaj formation. The geology is simple and

essentially uniform. In the upper 1-2 m, there is an overburden of

weathered clay shale of sandy nature and low cohesion. The limestone

formation below this has a thickness of 6-25 m; the bedding planes are

horizontal or sub-horizontal and crossed by some nearly vertical joints as

shown in Fig. 1. The upper part of limestone deposit is highly fractured

causing hole-collaring problems during drilling. The quarry is mined in

one bench. Limestone rock is medium-hard and has compressive strength

of 87 MPa and density is 2.66 tons/m3.


85

Fig. 1. Bench view of quarry, the upper fractured zone and horizontal bedding planes are

clearly visible.

Drilling is done with heavy duty down-the-hole hammer drill to a

preset blasting pattern. The blasting parameters are designed to suit the

rock conditions and gradation requirements. The holes are charged with

primed cartridge at the bottom with Shock-tube for detonation. ANFO is

filled as column charge. Two types of high explosives are used;

Gelatinous dynamite and Emulite. Each hole contains 15 kg of high

explosive and 60 kg of ANFO. Other blasting parameters are given in

Table 1.

Table 1. Blasting parameters.

Parameters Description

Hole diameter 104 mm

Bench Height 12 meters

Sub-drilling 0.5 meter

Burden 3 meter

Spacing 4 meter

Stemming 3 meter

Blasting Pattern Rectangular

Initiation System Nonel or Shock-tube

Powder Factor 0.5 kg / m3


3.2 Image Acqusition

Image acquisition of blasted rock for size distribution analysis is the

most critical phase of the analysis. Important issues in image sampling

are: The location of the image, the image angle from the surface of the

muckpile, and the scale of the image. In order to obtain good images,

which are both capable of being analyzed and representative of the entire

rock assemblage, sampling strategies must be carefully considered.

The location of image taking is important, and there are two

sampling methods, random and systematic. Both methods have been used

for this investigation. Another consideration is the angle of the surface

being photographed. Ideally, the surface should be perpendicular to the

camera lens.

Fig. 2. Typical image taken in the field for calculation of size distribution.

A digital camera was used to get the images of the blasted muck,

which were used in SPLIT. Images were taken randomly in the field and

a basket ball of 24 cm in diameter (9.4488 inch) was used to provide

scale in the images. Single scaling object was used in this investigation.

Total 15 images were taken for analysis.

3.3 Fragment Delineation

After the image acquisition the next step was to produce the binary

images from the acquired digital images that show the outlines of the

particles visible in the image. In this step Split-Desktop performs the


87

automatic delineation of the particles. As it can be observed from the Fig.

3b, the binary image actually allows three color levels: white for

particles, black for boundaries and fines, and gray for areas that do not

count in the size distribution such as the scaling object.

Fig. 3a. Grey-scale image Fig. 3b. Delineated binary image.

The three most important delineation parameters are Noise size,

Watershed ratio and Gradient ratio[6]

.

Noise Size: The noise size parameter is used to determine the size,

in pixels, of the smallest pixel grouping that is used in

the split algorithm. Noise size value may range from 3

to 90 and default value is 7. If the image contains

larger rock fragments and boulders, noise value may

set to as higher as 80 to 90 and if it contains finer

fragments, the value may reduce to 3.

The Noise size value for this investigation was found

empirically by using various values and finally 22 was

found best-fit for the images.

Watershed ratio: The watershed size ratio controls the number of

divisions made during the watershed algorithm which

is used to make additional divisions based on the

shape of the particles. The default value is 1.5, which

usually gives satisfactory result for most images.

Increasing this number makes fewer divisions and

decreasing it makes more. This value can be changed

typically between 0.33 and 3. In this investigation,

watershed ratio was set at 1.85.

Gradient ratio: The gradient is a numerical measure of grayscale

change from light to dark. The typical average


Gradient Ratio is 0.14. A higher value will create

fewer dividing lines and a lower value will create

more. The gradient ratio for this analysis was set at

0.18.

3.4 Binary Image Editing

Editing of the binary images is often required to enhance the

delineation of the individual fragment because the built-in delineation

algorithm of Split-Desktop not so precisely outline each and every

fragment so some manual editing must be done.

In this step the particle edges should be clearly outlined in a

continuous line, patches of fine material should be noted by filling in,

and the objects (such as sky, loading equipment and the floor in front of

the pile and scaling object) within the image that are not to be sized

should be removed.

3.5 Computation of Size Distribution Curves

Once the binary images have been completely edited, computation of

size distribution can be carried out. In this step, the distribution of fines

in each image can be calculated using two approaches Rosin-Rammler or

Schumann distribution. In the present study, a combination of these two

approaches was used to best-fit the fines distribution.

The final step and the most critical influence on the size calculation

is the Fines Estimation. Split-Desktop can measure particles

automatically, but in every image there is a point below the resolution of

the image where particles can no longer be “seen" and delineated. At this

point, Split-Desktop will estimate the remaining finer material. The

"fines" cutoff chiefly depends on the resolution in pixels/unit of the

image. Since the black pixels in the image represent both fines and

outlines of particles, a percent of these pixels is included in the fines

calculation. This percentage of black to be counted as fines can vary for

each muckpile and can be adjusted by the user[6]

.

For the images that contain too much fines, the High option can be

selected and also other options such as None, Low and Medium can be

selected accordingly depending upon the fines percentage in each image.


89

4. Discussion of Results

The seven most representative images of blasted muckpile were

analyzed and mean values were obtained. The obtained size distribution

curve is shown in Fig. 4.

Fig. 4. Size distribution results.

The percentage values, Rosin-Rammler uniformity index and mean

fragment size are given in Tables 2 and 3.

Table 2. Cumulative percent passing.

Size [mm] % Passing

2000 100

1000 99.02

750 96.04

500 85.78

250 62.81

125 45.46


Table 3. Fragment size characteristics.

Size fractions Size (mm)

P10 2.08

P20 11.66

P30 50.79

P40 102.15

P50 149.76

P60 225.02

P70 318.24

P80 426.31

P90 566.48

Top-Size 1057.44

Rosin-Rammler

uniformity index 0.81

Mean fragment size 149.76 mm

Table 2. Contd.

Size [mm] % Passing

100 39.43

75 33.46

53 30.36

37.5 27.56

26.5 25.02

19 22.82

13.2 20.66

9.5 18.94

6.7 17.31

4.75 15.86


91

5. Conclusion

The results obtained from the analysis of muckpile images using

Split-Desktop shows that the mean fragment size is 149.76 mm and P20,

P80, and Top-size are 11.66 mm, 426.31 mm and 1057.44 mm

respectively. The primary crusher installed at the quarry accepts the feed

size as large as 1000 mm and crush down to the 30 mm. As the results

indicate that approximately 25% of the fragments are below 30 mm;

hence the fragments do not require crushing and pass the primary crusher

screen smoothly and effortlessly. Results also indicate that only 1% of

the material is above 1000 mm therefore it requires secondary breakage.

The Rosin-Rammler uniformity index of the entire muckpile is 0.81.

This index is generally used to approximate the size distribution of rock

in blasted muckpiles. The value ranges between 0.5 (very non-uniform)

and 2 (very uniform). So the obtained index value confirms non-uniform

size distribution. Non-uniform size distribution affects the loading and

hauling operations and crusher’s efficiency.

As the results indicate that 25% fragments are below 30 mm, which

is product size of primary crusher, this percentage can be enhanced by

optimizing the overall blasting operation. The Burden and spacing are

two most important factors in the blasting because these factors can be

adjusted to obtain required fragmentation. Proper explosive in an

appropriate quantity can also results in good fragmentation and reduce

the overall cost of production.

Acknowledgment

The authors would like to express their sincere appreciation to

Engineer Mushtaq Abro, Deputy Manager at Dewan Cement Ltd, for his

help in data collection and image taking which are vital for this research

work and also thanks to every one at Department of Mining Engineering,

MUET Jamshoro, Pakistan.

References

[1] Esen, S. and Bilgin, H.A., “Effect of Explosive on Fragmentation”, (http://www.-

metsominerals.com/inetMinerals/mm_proc.nsf/WebWID/WTB-060320-2256F-60F1C/$File/esen_fragmentation_2001.pdf).

[2] Jimeno, C.L., Jimeno, E.L. and Carcedo, F.J.A., “Drilling and Blasting of Rocks”, A.A.

Balkema, Rotterdam, Netherlands (1995).


[3] Ozkahraman, H.T., “Fragmentation Assessment and Design of Blast Pattern at Goltas

Limestone Quarry, Turkey (Technical Note)”, International Journal of Rock Mechanics & Mining Sciences, Volume 43, pp: 628-633 (2006).

[4] Franklin, J.A., Kemeny, J.M. and Girdner K.K., “Evolution of Measuring Systems: A

review”, Proceedings of the Fragblast-5 Workshop on Measurement of Blast

Fragmentation, A.A. Balkema, Montreal, Quebec, Canada, pp. 47-52, August (1996).

[5] Split Engineering, LLC, Tucson, Arizona, USA, “Split-Desktop Software Manual”.

[6] Bobo, T., “What’s New with the Digital Image Analysis Software Split-Desktop®?” Split

Engineering, LLC, Tucson, Arizona, USA.


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Measurement of Size Distribution of Blasted Rock Using Digital Image Processing

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